#   Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import unittest

import numpy as np
from get_test_cover_info import (
    XPUOpTestWrapper,
    create_test_class,
    get_xpu_op_support_types,
)
from op_test_xpu import XPUOpTest

import paddle
from paddle import base
from paddle.base import Program, program_guard

paddle.enable_static()


class XPUTestSqueezeOp(XPUOpTestWrapper):
    def __init__(self):
        self.op_name = "squeeze"
        self.use_dynamic_create_class = False

    # Correct: General.
    class TestSqueezeOp(XPUOpTest):
        def setUp(self):
            self.op_type = "squeeze"
            self.__class__.op_type = "squeeze"
            self.use_mkldnn = False
            self.init_dtype()
            self.init_test_case()
            self.inputs = {
                "X": np.random.random(self.ori_shape).astype(self.dtype)
            }
            self.init_attrs()
            self.outputs = {
                "Out": self.inputs["X"].reshape(self.new_shape),
            }

        def init_dtype(self):
            self.dtype = self.in_type

        def test_check_output(self):
            place = paddle.XPUPlace(0)
            self.check_output_with_place(place)

        def test_check_grad(self):
            place = paddle.XPUPlace(0)
            if self.dtype == np.bool_:
                return
            else:
                self.check_grad_with_place(place, ['X'], 'Out')

        def init_test_case(self):
            self.ori_shape = (1, 3, 1, 40)
            self.axes = (0, 2)
            self.new_shape = (3, 40)

        def init_attrs(self):
            self.attrs = {"axes": self.axes}

    # Correct: There is mins axis.
    class TestSqueezeOp1(TestSqueezeOp):
        def init_test_case(self):
            self.ori_shape = (1, 3, 1, 40)
            self.axes = (0, -2)
            self.new_shape = (3, 40)

    # Correct: No axes input.
    class TestSqueezeOp2(TestSqueezeOp):
        def init_test_case(self):
            self.ori_shape = (1, 20, 1, 5)
            self.axes = ()
            self.new_shape = (20, 5)

    # Correct: Just part of axes be squeezed.
    class TestSqueezeOp3(TestSqueezeOp):
        def init_test_case(self):
            self.ori_shape = (6, 1, 5, 1, 4, 1)
            self.axes = (1, -1)
            self.new_shape = (6, 5, 1, 4)

    # Correct: The demension of axis is not of size 1 remains unchanged.
    class TestSqueezeOp4(TestSqueezeOp):
        def init_test_case(self):
            self.ori_shape = (6, 1, 5, 1, 4, 1)
            self.axes = (1, 2)
            self.new_shape = (6, 5, 1, 4, 1)


class TestSqueezeOpError(unittest.TestCase):
    def test_errors(self):
        paddle.enable_static()
        with program_guard(Program(), Program()):
            # The input type of softmax_op must be Variable.
            x1 = base.create_lod_tensor(
                np.array([[-1]]), [[1]], paddle.XPUPlace(0)
            )
            self.assertRaises(TypeError, paddle.squeeze, x1)
            # The input axes of squeeze must be list.
            x2 = paddle.static.data(name='x2', shape=[4], dtype="int32")
            self.assertRaises(TypeError, paddle.squeeze, x2, axes=0)
            # The input dtype of squeeze not support float16.
            x3 = paddle.static.data(name='x3', shape=[4], dtype="float16")
            self.assertRaises(TypeError, paddle.squeeze, x3, axes=0)


support_types = get_xpu_op_support_types("squeeze")
for stype in support_types:
    create_test_class(globals(), XPUTestSqueezeOp, stype)

if __name__ == "__main__":
    unittest.main()
